In the texting and messaging environment, it has become popular for users to include images in word-based text. For example, it is common for users to enter text-based representations of images, known as emoticons, to express emotion such as :-) or ;-p [typical in the west] or ({circumflex over ( )}_{circumflex over ( )}) [typical in Asia]. More recently, small character sized images, called emojis have become popular. Stickers have also become popular. A sticker is a detailed illustration of a character that represents an emotion or action that is a mix of cartoons and emojis.
As of October 2010, the Unicode (6.0) standard allocates 722 codepoints as descriptions of emojis (examples include U+1F60D: Smiling face with heart shaped eyes and U+1F692: Fire engine). It is typical for messaging services (eg. Facebook, Whatsapp) to design their own set of images, which they use to render each of these unicode characters so that they may be sent and received. Additionally, both Android (4.1+) and iOS (5+) provide representations of these characters natively as part of the default font.
Although it is popular to input emojis, it remains difficult to do so, because the user has to discover appropriate emojis and, even knowing the appropriate emoji, has to navigate through a great number of possible emojis to find the one they want to input.
Keyboards and messaging clients have tried to reduce the problem by including an emoji selection panel, in which emojis are organised into several categories which can be scrolled through. Although the emojis have been grouped into relevant categories, the user is still required to search through the emojis of that category in order to find the emoji they want to use. Furthermore, some emojis may not be easily classified, making it more difficult for the user to decide in which category they should search for that emoji.
There are known solutions which attempt to reduce further the burden of inputting emojis. For example, several messaging clients will replace automatically certain shorthand text with images. For example, Facebook Messenger will convert the emoticon :-) to a picture of a smiling face and will convert the short hand text sequence, (y), to a picture of a thumbs up when the message is sent.
Additionally, the Google Android Jellybean keyboard will offer an emoji candidate when the user types, exactly, a word corresponding to a description of that emoji, e.g. if ‘snowflake’ is typed, the picture  is offered to the user as candidate input.
These known solutions to reduce the burden of emoji input still require a user to provide the shorthand text that identifies the emoji or to type the exact description of the emoji. Although the known systems obviate the requirement to scroll through screens of emojis, they still require the user to explicitly and correctly identify the emoji they wish to enter.
It is an object of the present invention to address the above-mentioned problem and reduce the burden of image (e.g. emoji, emoticon or sticker) and label input in the messaging/texting environment.